Wind power has become the most popular renewable energy promising to displace traditional pollutive thermal power generation due to rich resources, mature technology, and zero emission. Global wind turbine installation had reached 318 GW by end of 2013. With rapid installation increase of wind farms, expensive O&M (operation and maintenance) cost and downtime electricity sale loss develop to be more and more pressing issues. Taking a 2 MW wind turbine as example, as evaluated by master thesis of KTH, about 248.4 kUSD annual cost arises, incl. 242.7 kUSD O&M cost and 5.7 kUSD electricity sale loss.
Under such environment, it's desired by the market to develop a kind of condition monitoring system (CMS) product which is able to real time detect the defects of wind turbine, analyze the fault type, and position the defective part, before the wind turbine evolves to real failure. Now the available products in market with such functionality are all based on additional sensors, e.g. vibration, acoustic, etc. These intrusive sensors not only largely increase the capital cost, but also cause recertification of wind turbines, both of which are undesirable for wind farm operators.